Get Started with Amazon SageMaker - Amazon SageMaker
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Get Started with Amazon SageMaker

Before you can use Amazon SageMaker, you must sign up for an Amazon account and create an IAM admin user by following the steps in Set Up Amazon SageMaker Prerequisites.

Amazon SageMaker Studio Lab does not require an Amazon account or IAM integration.

After you complete these tasks, continue to one of the following topics, depending on your use case.

  • Onboard to Amazon SageMaker Domain: Follow these steps to create a Domain, which gives you access to Amazon SageMaker Studio and RStudio on Amazon SageMaker. For more information about Domains, see Amazon SageMaker Machine Learning Environments.

  • SageMaker JumpStart: Follow these steps to start working with SageMaker JumpStart and learn about SageMaker features and capabilities through curated one-click solutions, example notebooks, and pretrained models that you can deploy. To use SageMaker JumpStart, which is a feature of Amazon SageMaker Studio, you must first onboard to an Amazon SageMaker Domain.

  • Get Started with Amazon SageMaker Notebook Instances: Follow these steps to train and deploy Machine Learning (ML) models using SageMaker notebook instances. SageMaker notebook instances help create the environment by initiating Jupyter servers on Amazon Elastic Compute Cloud (Amazon EC2) and providing preconfigured kernels. For more information, see Use Amazon SageMaker Notebook Instances.

  • Amazon SageMaker Studio Lab: Follow these steps to start working with Amazon SageMaker Studio Lab. Studio Lab is a free service that gives you access to Amazon compute resources, in an environment based on open-source JupyterLab, without requiring an Amazon account.